Fraud and identity theft are large and growing problems in the financial industry. From an investigative standpoint, each new case has to be treated separately from all others and investigated after the fact. Financial transactional systems are designed for performance and reliability, not auditing. Because of storage constraints and the load on the transactional systems, investigators often required weeks or months to investigate a single incident. Meanwhile, the dishonest person who committed the first fraud has had the opportunity to repeat the offense dozens or hundreds of times.
In the past, fraud research has generally been performed from the original transactional system, which typically archives a tremendous amount of data regarding financial transactions, on the order of hundreds of terabytes or more. This renders impractical the possibility of aggregating data to automate searches for fraud rings and other organized inappropriate activity. To make matters worse, such financial transaction information may originate from more than one source and be provided in more than one format. This situation is particularly common where the financial institution is a conglomerate of smaller disparate financial institutions each using its own different data management system.